| dc.description.abstract | There has been an increasing disparity between the lending rates and the deposit rates in Kenya over the last decade. In the Kenyan history, 1982 saw the lowest interest rate spread at 2.3% with the highest spread experienced in 1996 at 16.2%.In 2005 after decreasing to 7.8% from 10.10% in 2004, the spread assumed an upward trend rising to 9.81% in 2010. Despite policy interventions and structural reforms in the financial sector, the spread has consistently risen from the year 2003 up to 2010 with an insignificant drop in year 2011. The causes of this persistently increasing interest rate spread despite the many reforms are not known. This study analyzed the determinants of interest rate spreads in Kenya by focusing on eight banking institutions that significantly control deposits and loans market in the past decade. The study used panel least squares estimation technique on annual data between 2002 to 2011 to analyze the determinants of interest rates spreads as grouped in literature under: Bank-Specific Factors, Industry-specific data and Macroeconomic factors. The main objective of the study was to analyze the determinants of interest rate spread in the Kenyan economy. Its specific objectives were to establish the bank specific factors that influence the interest rate spread, to investigate the macroeconomic factors that influence the interest rate spread and to examine the industry specific factors that influence the interest rate spread in Kenya. The interest rate spread experienced in Kenya over the last decade is higher than that of emerging and developed economies. According to vision 2030 it is recommended at an acceptable rate of five per cent for the purpose of mobilizing savings and credit expansion. Although many efforts have been undertaken in the financial services sector, this vision has not been attained but instead an upward trajectory has been witnessed. The study was carried out using panel quantitative data analysis which involved the panel unit root test; Levin-Lin Chu and Im-Pesaran-Shin tests among other diagnostic tests including normality test, heteroscedasticity, Multicollinearity and Hausman tests. The study also used descriptive statistics such as mean, standard deviation. Due to the nature of the study STATA software was used to analyze the data. The analyzed data was then presented using figures, tables and graphs. Explanatory research design was used. The results revealed that, among the bank specific factors non interest income (0.045), nonperforming loans (0.002) and loan asset ratio (0.004) were significant. In addition among the industry specific factors, liquid asset ratio (0.042) was significant. While the finding revealed that only Treasury bill (0.001) was significant among the macroeconomic factors. The results mean that all those variables which have a P value of below 0.05 are significant for the study and cause the interest rate spreads to widen while those variables whose P values were above 0.05 are statistically insignificant for the study and have little effect on the interest rate spreads in Kenya. The study concluded that non interest income, nonperforming loans, loan asset ratio, Liquid asset ratio and treasury bills rate are the determinants of interest rates spreads in Kenya. It recommends that, the high responsiveness of banks spreads to the Treasury bills rate suggests that private borrowing should be reduced by the government in order to allow banks to lend to the general public since the financial institutions will rather lend to the Government through risk free securities than to general public, banks must continue to seriously deal with the issues of the high levels of non- performing loans and the diseconomies of scale in their operations and if there is to be any success in reducing interest rate spreads to support long- term economic growth, the competitive environment in the banking system must be enhanced. | en_US |
